Multi-Agent Coordination

Compare the canonical multi-agent orchestration patterns — sequential, group chat, supervisor, and human-in-the-loop — and learn which problem shape calls for which topology.

Understand why isolation — ephemeral environments, scoped identities, branch-per-task — is the precondition for running agents in parallel without them stepping on each other or on production state.

Learn how to detect when two agents have produced incompatible outputs and pick the right resolution strategy — last-writer-wins, merge, escalate, or replay — based on the cost of being wrong.

When control passes between agents — or from an agent to a human — the receiving party needs three things: what was decided, why, and what the next expected outcome is. Learn the artifacts and structures that make handoffs auditable.

Learn the failure taxonomy for agent runs — hard failure, partial success, stalled, and silently wrong — and match observable signals (HTTP codes, traces, eval scores) to each mode so the orchestrator can react correctly.

Once a failure is detected, the orchestrator must choose between retry, resume from checkpoint, rollback, and human escalation. Learn how reversibility, blast radius, and idempotency drive that choice.

Treat agents as first-class managed services with versions, identities, and deprecation windows. Learn the add/update/retire lifecycle, why versioning matters, and how to retire an agent without orphaning its consumers.